Performance of the Remotely-Derived Products in Monitoring Gross Primary Production across Arid and Semi-Arid Ecosystems in Northwest China

Abstract

As an important component to quantify the carbon budget, accurate evaluation of terrestrial gross primary production (GPP) is crucial for large-scale applications, especially in dryland ecosystems. Based on the in situ data from six flux sites in northwestern China from 2014 to 2016, this study compares seasonal and interannual dynamics of carbon fluxes between these arid and semi-arid ecosystems and the atmosphere. Meanwhile, the reliability of multiple remotely-derived GPP products in representative drylands was examined, including the Breathing Earth System Simulator (BESS), the Moderate Resolution Imaging Spectroradiometer (MODIS) and data derived from the OCO-2 solar-induced chlorophyll fluorescence (GOSIF). The results indicated that the carbon fluxes had clear seasonal patterns, with all ecosystems functioning as carbon sinks. The maize cropland had the highest GPP with 1183 g C m−2 y−1. Although the net ecosystem carbon exchange (NEE) in the Tamarix spp. ecosystem was the smallest among these flux sites, it reached 208 g C m−2 y−1. Furthermore, distinct advantages of GOSIF GPP (with R2 = 0.85–0.98, and RMSE = 0.87–2.66 g C m−2 d−1) were found with good performance. However, large underestimations in three GPP products existed during the growing seasons, except in grassland ecosystems. The main reasons can be ascribed to the uncertainties in the key model parameters, including the underestimated light use efficiency of the MODIS GPP, the same coarse land cover product for the BESS and MODIS GPP, the coarse gridded meteorological data, and distribution of C3 and C4 plants. Therefore, it still requires more work to accurately quantify the GPP across these dryland ecosystems.

Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment

“…Developed by Li and Xiao [67], this product has a spatial resolution of 0.05° and offers temporal resolutions of 8 days, monthly, and annually. The GOSIF GPP dataset has been validated through comparisons with independent flux tower data, demonstrating high precision and the ability to effectively represent spatiotemporal variations in large-scale GPP [68]. This validation, which considered each biome separately, confirmed the dataset's accuracy in representing photosynthetic activity, particularly in grassland ecosystems.…”

Quantifying responses of net primary productivity to agricultural expansion in drylands

“…More errors arise from the input of FPAR and LUE. Many studies have shown that the FPAR and maximum LUE input by MOD17 are underestimated, making the MOD17 data underestimated compared to other productivity productions (Abdi et al, 2019; Gu et al, 2020; Sjöström et al, 2013; Wang et al, 2017;Zhu et al, 2016; Zhu et al, 2018). Ignoring the saturation led to an overestimation of MOD17 in high FPAR areas (Propastin, Ibrom, Knohl, & Erasmi, 2012; Zhu et al, 2018).…”

Impacts of Heat and Drought on Gross Primary Productivity in China

“…It should be noted that the eight subareas are used for geographical zoning rather than vegetation type zoning. The temperate desert region (R1), the temperate grassland region (R2), and the climatic range of the alpine vegetation region on the Qinghai-Tibet Plateau (R3) are restricted by insufficient precipitation or low temperatures and have sparse vegetation and low GPP levels [47][48][49]. Precipitation in the temperate coniferous and deciduous forest mixed forest region (R7) and the cold temperate coniferous forest region (R8) is abundant; vegetation growth in these regions is mainly restricted by temperature and radiation, and the vegetation coverage and GPP are relatively high [50].…”